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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 26 Nov 2007 12:50:18 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/26/t1196106073tro2yts241a43mj.htm/, Retrieved Fri, 03 May 2024 02:56:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6651, Retrieved Fri, 03 May 2024 02:56:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [] [2007-11-26 19:50:18] [079615521100262cd8b5675a0217a3b1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
88.74
88.92
88.77
89.17
89.61
89.52
89.74
89.40
89.36
89.38
89.36
89.29
89.59
89.79
89.86
90.21
90.37
90.19
90.33
90.22
90.42
90.54
90.73
91.02
91.19
91.53
91.88
92.06
92.32
92.67
92.85
92.82
93.46
93.23
93.54
93.29
93.20
93.60
93.81
94.62
95.22
95.38
95.31
95.30
95.57
95.42
95.53
95.33
95.90
96.06
96.31
96.34
96.49
96.22
96.53
96.50
96.77
96.66
96.58
96.63
97.06
97.73
98.01
97.76
97.49
97.77
97.96
98.23
98.51
98.19
98.37
98.31
98.60
98.97
99.11
99.64
100.03
99.98
100.32
100.44
100.51
101.00
100.88
100.55
100.83
101.51
102.16
102.39
102.54
102.85
103.47
103.57
103.69
103.50
103.47
103.45
103.48
103.93
103.89
104.40
104.79
104.77
105.13
105.26
104.96
104.75
105.01
105.15
105.20
105.77
105.78
106.26
106.13
106.12
106.57
106.44
106.54
Dataseries Y:
Download CSV
Histogram 
88.95
88.81
88.90
90.15
90.92
90.78
90.81
89.46
89.22
88.89
89.41
89.59
90.25
90.20
90.27
90.71
91.18
90.66
89.72
88.72
88.91
89.15
89.15
89.08
89.28
89.47
89.53
90.72
90.91
91.38
91.49
90.90
90.93
90.57
91.28
90.83
91.50
91.58
92.49
94.16
95.46
95.80
95.32
95.41
95.35
95.68
95.59
94.96
96.92
96.06
96.59
96.67
97.27
96.38
96.47
96.05
96.76
96.51
96.55
95.97
97.00
97.46
97.90
98.42
98.54
99.00
98.94
99.02
100.07
98.72
98.73
98.04
99.08
99.22
99.57
100.44
100.84
100.75
100.49
99.98
99.96
99.76
100.11
99.79
100.29
101.12
102.65
102.71
103.39
102.80
102.07
102.15
101.21
101.27
101.86
101.65
101.94
102.62
102.71
103.39
104.51
104.09
104.29
104.57
105.39
105.15
106.13
105.46
106.47
106.62
106.52
108.04
107.15
107.32
107.76
107.26
107.89

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6651&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6651&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-170.611896618414333
-160.635589427287293
-150.659157923059857
-140.68489749192771
-130.709591597824924
-120.73265261594754
-110.755016924434616
-100.777112695988149
-90.800049886889665
-80.821249730271362
-70.842542388521808
-60.859810525769683
-50.878047265799591
-40.895720063456507
-30.914965751676461
-20.93911322112513
-10.96146543926607
00.983253719161354
10.956075168431018
20.929821176292773
30.901132081636401
40.873037648664441
50.84583354536084
60.815448072967048
70.789072996911092
80.76250683867604
90.73627900995695
100.712231853372754
110.685321342690432
120.659725012368641
130.632654391732687
140.607084591475163
150.581107409517671
160.555927075794851
170.529504536050169

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-17 & 0.611896618414333 \tabularnewline
-16 & 0.635589427287293 \tabularnewline
-15 & 0.659157923059857 \tabularnewline
-14 & 0.68489749192771 \tabularnewline
-13 & 0.709591597824924 \tabularnewline
-12 & 0.73265261594754 \tabularnewline
-11 & 0.755016924434616 \tabularnewline
-10 & 0.777112695988149 \tabularnewline
-9 & 0.800049886889665 \tabularnewline
-8 & 0.821249730271362 \tabularnewline
-7 & 0.842542388521808 \tabularnewline
-6 & 0.859810525769683 \tabularnewline
-5 & 0.878047265799591 \tabularnewline
-4 & 0.895720063456507 \tabularnewline
-3 & 0.914965751676461 \tabularnewline
-2 & 0.93911322112513 \tabularnewline
-1 & 0.96146543926607 \tabularnewline
0 & 0.983253719161354 \tabularnewline
1 & 0.956075168431018 \tabularnewline
2 & 0.929821176292773 \tabularnewline
3 & 0.901132081636401 \tabularnewline
4 & 0.873037648664441 \tabularnewline
5 & 0.84583354536084 \tabularnewline
6 & 0.815448072967048 \tabularnewline
7 & 0.789072996911092 \tabularnewline
8 & 0.76250683867604 \tabularnewline
9 & 0.73627900995695 \tabularnewline
10 & 0.712231853372754 \tabularnewline
11 & 0.685321342690432 \tabularnewline
12 & 0.659725012368641 \tabularnewline
13 & 0.632654391732687 \tabularnewline
14 & 0.607084591475163 \tabularnewline
15 & 0.581107409517671 \tabularnewline
16 & 0.555927075794851 \tabularnewline
17 & 0.529504536050169 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6651&T=1

[TABLE]
[ROW][C]Cross Correlation Function[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of X series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-17[/C][C]0.611896618414333[/C][/ROW]
[ROW][C]-16[/C][C]0.635589427287293[/C][/ROW]
[ROW][C]-15[/C][C]0.659157923059857[/C][/ROW]
[ROW][C]-14[/C][C]0.68489749192771[/C][/ROW]
[ROW][C]-13[/C][C]0.709591597824924[/C][/ROW]
[ROW][C]-12[/C][C]0.73265261594754[/C][/ROW]
[ROW][C]-11[/C][C]0.755016924434616[/C][/ROW]
[ROW][C]-10[/C][C]0.777112695988149[/C][/ROW]
[ROW][C]-9[/C][C]0.800049886889665[/C][/ROW]
[ROW][C]-8[/C][C]0.821249730271362[/C][/ROW]
[ROW][C]-7[/C][C]0.842542388521808[/C][/ROW]
[ROW][C]-6[/C][C]0.859810525769683[/C][/ROW]
[ROW][C]-5[/C][C]0.878047265799591[/C][/ROW]
[ROW][C]-4[/C][C]0.895720063456507[/C][/ROW]
[ROW][C]-3[/C][C]0.914965751676461[/C][/ROW]
[ROW][C]-2[/C][C]0.93911322112513[/C][/ROW]
[ROW][C]-1[/C][C]0.96146543926607[/C][/ROW]
[ROW][C]0[/C][C]0.983253719161354[/C][/ROW]
[ROW][C]1[/C][C]0.956075168431018[/C][/ROW]
[ROW][C]2[/C][C]0.929821176292773[/C][/ROW]
[ROW][C]3[/C][C]0.901132081636401[/C][/ROW]
[ROW][C]4[/C][C]0.873037648664441[/C][/ROW]
[ROW][C]5[/C][C]0.84583354536084[/C][/ROW]
[ROW][C]6[/C][C]0.815448072967048[/C][/ROW]
[ROW][C]7[/C][C]0.789072996911092[/C][/ROW]
[ROW][C]8[/C][C]0.76250683867604[/C][/ROW]
[ROW][C]9[/C][C]0.73627900995695[/C][/ROW]
[ROW][C]10[/C][C]0.712231853372754[/C][/ROW]
[ROW][C]11[/C][C]0.685321342690432[/C][/ROW]
[ROW][C]12[/C][C]0.659725012368641[/C][/ROW]
[ROW][C]13[/C][C]0.632654391732687[/C][/ROW]
[ROW][C]14[/C][C]0.607084591475163[/C][/ROW]
[ROW][C]15[/C][C]0.581107409517671[/C][/ROW]
[ROW][C]16[/C][C]0.555927075794851[/C][/ROW]
[ROW][C]17[/C][C]0.529504536050169[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6651&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-170.611896618414333
-160.635589427287293
-150.659157923059857
-140.68489749192771
-130.709591597824924
-120.73265261594754
-110.755016924434616
-100.777112695988149
-90.800049886889665
-80.821249730271362
-70.842542388521808
-60.859810525769683
-50.878047265799591
-40.895720063456507
-30.914965751676461
-20.93911322112513
-10.96146543926607
00.983253719161354
10.956075168431018
20.929821176292773
30.901132081636401
40.873037648664441
50.84583354536084
60.815448072967048
70.789072996911092
80.76250683867604
90.73627900995695
100.712231853372754
110.685321342690432
120.659725012368641
130.632654391732687
140.607084591475163
150.581107409517671
160.555927075794851
170.529504536050169


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',xlab='Lag (k)'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Cross Correlation Function',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
a<-table.element(a,par7)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'k',header=TRUE)
a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
a<-table.row.end(a)
mylength <- length(r$acf)
myhalf <- floor((mylength-1)/2)
for (i in 1:mylength) {
a<-table.row.start(a)
a<-table.element(a,i-myhalf-1,header=TRUE)
a<-table.element(a,r$acf[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')